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Relatively simple low-pass-filtering algorithm suppresses high-frequency noise in digitally sampled signal. Algorithm derived from convolution of signal with causal exponential. Filter implemented by algorithm does not introduce phase shift. Algorithm applies forward convolution in time followed by backward convolution in time, and phase shift in second convolution cancels phase shift in first convolution.
A method for calculating the increase in received telemetry signal power required to compensate for the use of a radio frequency interference (RFI) filter in front of the DSN receiving system low-noise amplifier is described. The telemetry system for which the degradation is calculated is an uncoded PCM/PM system in which the NRZ data directly modulates the carrier at a modulation level which leaves a discrete carrier. A phase-locked loop in the RF receiver tracks the discrete carrier and coherently demodulates the PCM data. The RFI filter may be a series of Butterworth, Tchebychev, or Bessel low-pass, high-pass, band-pass, or band-reject filters, each with arbitrary bandwidth, number of poles, and, for band-pass or band-reject filters, resonant frequency. The only restriction is that the RFI filter must have only simple poles. Numerical results are presented for the RFI filters the DSN plans to place in front of the S-band FET, S-band maser, and X-band maser low noise amplifiers. The main conclusion is that the filters will produce negligible degradation at data rates below 4 Mbps.
The equations for large-eddy simulation (LES) are derived formally by applying a spatial filter to the Navier-Stokes equations. The filter width as well as the details of the filter shape are free parameters in LES, and these can be used both to control the effective resolution of the simulation and to establish the relative importance of different portions of the resolved spectrum. An analogous, but less well justified, approach to filtering is more or less universally used in conjunction with LES using finite-difference methods. In this approach, the finite support provided by the computational mesh as well as the wavenumber-dependent truncation errors associated with the finite-difference operators are assumed to define the filter operation. This approach has the advantage that it is also 'automatic' in the sense that no explicit filtering: operations need to be performed. While it is certainly convenient to avoid the explicit filtering operation, there are some practical considerations associated with finite-difference methods that favor the use of an explicit filter. Foremost among these considerations is the issue of truncation error. All finite-difference approximations have an associated truncation error that increases with increasing wavenumber. These errors can be quite severe for the smallest resolved scales, and these errors will interfere with the dynamics of the small eddies if no corrective action is taken. Years of experience at CTR with a second-order finite-difference scheme for high Reynolds number LES has repeatedly indicated that truncation errors must be minimized in order to obtain acceptable simulation results. While the potential advantages of explicit filtering are rather clear, there is a significant cost associated with its implementation. In particular, explicit filtering reduces the effective resolution of the simulation compared with that afforded by the mesh. The resolution requirements for LES are usually set by the need to capture most of the energy-containing eddies, and if explicit filtering is used, the mesh must be enlarged so that these motions are passed by the filter. Given the high cost of explicit filtering, the following interesting question arises. Since the mesh must be expanded in order to perform the explicit filter, might it be better to take advantage of the increased resolution and simply perform an unfiltered simulation on the larger mesh? The cost of the two approaches is roughly the same, but the philosophy is rather different. In the filtered simulation, resolution is sacrificed in order to minimize the various forms of numerical error. In the unfiltered simulation, the errors are left intact, but they are concentrated at very small scales that could be dynamically unimportant from a LES perspective. Very little is known about this tradeoff and the objective of this work is to study this relationship in high Reynolds number channel flow simulations using a second-order finite-difference method.
As new analytical instruments and techniques emerge with increased dimensionality, a corresponding need is seen for data processing logic which can appropriately address the data. Two-dimensional measurements reveal enhanced unknown mixture analysis capability as a result of the greater spectral information content over two one-dimensional methods taken separately. It is noted that two-dimensional convolute integers are merely an extension of the work by Savitzky and Golay (1964). It is shown that these low-pass, high-pass and band-pass digital filters are truly two-dimensional and that they can be applied in a manner identical with their one-dimensional counterpart, that is, a weighted nearest-neighbor, moving average with zero phase shifting, convoluted integer (universal number) weighting coefficients.
A need exists for digitized information pertaining to linear features such as roads, streams, water bodies and agricultural field boundaries as component parts of a data base. For many areas where this data may not yet exist or is in need of updating, these features may be extracted from remotely sensed digital data. This paper examines two approaches for identifying linear features, one utilizing raw data and the other classified data. Each approach uses a series of data enhancement procedures including derivation of standard deviation values, principal component analysis and filtering procedures using a high-pass window matrix. Just as certain bands better classify different land covers, so too do these bands exhibit high spectral contrast by which boundaries between land covers can be delineated. A few applications for this kind of data are briefly discussed, including its potential in a Universal Soil Loss Equation Model.
Image Database computer program, IBASE, is general-purpose imagery-information system. Use accomplished either by commands or through hierarchy of menus. Analytical capabilities of IBASE include contigency tables, image filtering (low-, high-, and band-pass), proximity maps, clustering, histograms, regression, slope calculations, scaling, and Boolean manipulations. Also has interface to Cheshire Image Classification expert system. Written in FORTRAN 77.
A version of the dynamical adjustment procedure is generalized in order to make the procedure applicable to a diabatic model. In this new initialization procedure, backward adiabatic model integration is followed by forward diabatic model integration, with a high-frequency (low-pass) time filter in the form of the Euler backward time-differencing scheme applied throughout the integration. The new procedure was applied to the Goddard Laboratory for Atmospheres 4D data-assimilation system. It was found that, right from the beginning of the forecast integration, the forecast tendencies (and fields) were free of any noise due to imbalance in initial conditions, and the shocks related to an initial imbalance between model physics and dynamics, or the initial spinup effect, were practically removed.
The techniques considered make it possible to construct high performance low-pass wide-band, and medium-band filters at wavelengths in the range from 25 to 300 micrometers. Short wavelength rejection without appreciable loss at long wavelengths is achieved by means of small particle scattering. Spectral definition in the far infrared is obtained by cooling one or more crystalline materials to liquid-He or liquid-nitrogen temperatures. The problem of reflection losses at the various surfaces is solved by a new antireflection coating technique.
Optical filters with both narrow pass bands and high efficiencies fabricated to design specifications. Offer tremendous improvements in performance for number of optical (including infrared) systems. In fiber-optic and free-space communication systems, precise frequency discrimination afforded by narrow pass bands of filters provide higher channel capacities. In active and passive remote sensors like lidar and gas-filter-correlation radiometers, increased efficiencies afforded by filters enhance detection of small signals against large background noise. In addition, sizes, weights, and power requirements of many optical and infrared systems reduced by taking advantage of gains in signal-to-noise ratios delivered by filters.
Coplanar waveguide (CPW) low-pass filters made of YBa2Cu3O(7-delta) (YBCO) on LaAlO3 substrates, with dimensions suited for integrated circuits, were fabricated and packaged. A complete filter gives a true idea of the advantages and difficulties in replacing thin-film metal with a high-temperature superconductor in a practical circuit. Measured insertion losses in liquid nitrogen were superior to the loss of a similar thin-film copper filter throughout the 0- to 9.5-GHz passband. These results demonstrate the performance of fully patterned YBCO in a practical CPW structure after sealing in a hermetic package.
Noise, whether due to the image-gathering device or some other reason, reduces the visibility of fine features in an image. Several techniques attempt to mitigate the impact of noise by performing a low-pass filtering operation on the acquired data. This is based on the assumption that the uncorrelated noise has high-frequency content and thus will be suppressed by low-pass filtering. A result of this operation is that edges in a noisy image also tend to get blurred, and, in some cases, may get completely lost due to the low-pass filtering. In this paper, we quantitatively assess the impact of noise on fine feature visibility by using computer-generated targets of known spatial detail. Additionally, we develop a new scheme for noise-reduction based on the connectivity of edge-features. The overall impact of this scheme is to reduce overall noise, yet retain the high frequency content that make edge-features sharp.
Sandia National Laboratories (SNL) assessed the filtration performance of materials from Sierra Peaks to identify alternatives which may perform similarly to materials used in FDA-approved N95 respirators. This work is meant to characterize the aerosol performance of materials to give Sierra Peaks information for them to determine if they elect to submit masks made using these materials for follow-on N95 certification testing at an accredited facility. The R&D testbed used is a large-scale filtration system designed to test commercial filter boxes. System modifications were performed to simulate, where possible, parameters defined by the National Institute for Occupational Safety and Health (NIOSH) for certification of filter materials for N95 respirators (NIOSH 2019). The system is a pull-through design. Air enters through a Laminar Flow Element (LFE) and the volumetric flow is measured based on the pressure drop across the LFE. Pressure is measured via a Pressure Transducer (PT). The air then passes through a High Efficiency Particulate Air (HEPA) filter to purge the air of ambient airborne particulates. Test aerosol is injected into the flow shortly after and mixing is induced via a coarse mesh. The airflow is allowed to fully develop prior to arriving at the test section. The aerosol then passes through the test material mounted in a box in the test section. Pressure drop across the test article is measured and aerosol sampling probes measure the aerosol concentrations upstream and downstream of the sample. The air passes through a second HEPA filter prior to being exhausted to ambient by a blower. A Topas aerosol generator is used to produce the test aerosol from Sodium Chloride (NaC1) dissolved in deionized (DI) water. Generated aerosol passes through a heated mixing chamber and a desiccant dryer to produce nanosized solid-state particulates. A dilution loop allows for the aerosol concentration to be regulated. The aerosol sampling probes upstream and downstream of the test section are aligned with the flow path. These are ducted directly to the aerosol sizing and counting instruments. A Laser Aerosol Spectrometer (LAS) was used for data collection in the original configuration of the system and was also used for initial testing in this project. Because the lower measurement range for the LAS is 90 nanometers (nm), the LAS was switched out for a more complicated Scanning Mobility Particle Sizer (SMPS) spectrometer system. The SMPS is comprised of an Electrostatic Classifier (EC), Differential Mobility Analyzer (DMA), and a Condensation Particle Counter (CPC). This enabled data collection at 75 nm, the particle size called out in the NIOSH guidelines.
The characteristics of a potassium Faraday anomalous dispersion optical filter operating on the blue and near infrared transitions are calculated. The results show that the filter can be designed to provide high transmission, very narrow pass bandwidth, and low equivalent noise bandwidth. The Faraday anomalous dispersion optical filter (FADOF) provides a narrow pass bandwidth (about GHz) optical filter for laser communications, remote sensing, and lidar. The general theoretical model for the FADOF has been established in our previous paper. In this paper, we have identified the optimum operational conditions for a potassium FADOF operating on the blue and infrared transitions. The signal transmission, bandwidth, and equivalent noise bandwidth (ENBW) are also calculated.
One of the major technical problems deep-space optical communication (DSOC) systems need to solve is the isolation of the optical terminal from vibrations produced by the spacecraft navigational control system and by the moving parts of onboard instruments. Even under these vibration perturbations, the DSOC transceivers (telescopes) need to be pointed l000 fs of times more accurately than an RF communication system (parabolic antennas). Mechanical resonators have been extensively used to provide vibration isolation for groundbased, airborne, and spaceborne payloads. The effectiveness of these isolation systems is determined mainly by the ability of designing a mechanical oscillator with the lowest possible resonant frequency. The Low-Frequency Vibration Isolation Platform (LFVIP), developed during this effort, aims to reduce the resonant frequency of the mechanical oscillators into the sub-Hertz region in order to maximize the passive isolation afforded by the 40 dB/decade roll-off response of the resonator. The LFVIP also provides tip/tilt functionality for acquisition and tracking of a beacon signal. An active control system is used for platform positioning and for dampening of the mechanical oscillator. The basic idea in the design of the isolation platform is to use a passive isolation strut with an approximately equal to 100-mHz resonance frequency. This will extend the isolation range to lower frequencies. The harmonic oscillator is a second-order lowpass filter for mechanical disturbances. The resonance quality depends on the dissipation mechanisms, which are mainly hysteretic because of the low resonant frequency and the absence of any viscous medium. The LFVIP system is configured using the well-established Stewart Platform, which consists of a top platform connected to a base with six extensible struts (see figure). The struts are attached to the base and to the platform via universal joints, which permit the extension and contraction of the struts. The struts ends are connected in pairs to the base and to the platform, forming an octahedron. The six struts provide the vibration isolation due to the properties of mechanical oscillators that behave as second-order lowpass filters for frequencies above the resonance. At high frequency, the ideal second-order low-pass filter response is spoiled by the distributed mass and the internal modes of membrane and of the platform with its payload.
While the eddy covariance (EC) technique is a well-established method for measuring water fluxes (i.e., evaporation or 'evapotranspiration’, ET), the measurement is susceptible to many uncertainties. One such issue is the potential underestimation of ET when relative humidity (RH) is high (> 70%), due to low-pass filtering with some EC systems. Yet, this underestimation for different types of EC systems (e.g. open-path or closed-path sensors) has not been characterized for synthesis datasets such as the widely used FLUXNET2015 dataset. Here, we assess the RH-associated underestimation of latent heat fluxes (LE, or ET) from different EC systems for 163 sites in the FLUXNET2015 dataset. We found that the LE underestimation is most apparent during hours when RH is higher than 70%, predominantly observed at sites using closed-path EC systems, but the extent of the LE underestimation is highly site-specific. We then propose a machine learning based method to correct for this underestimation, and compare it to two energy balance closure based LE correction approaches (Bowen ratio correction, BRC, and attributing all errors to LE). Our correction increases LE by 189% for closed-path sites at high RH (> 90%), while BRC increases LE by around 30% for all RH conditions. Additionally, we assess the influence of these corrections on ET-based transpiration (T) estimates using two different ET partitioning methods. Results show opposite responses (increasing vs. slightly decreasing T-to-ET ratios, T/ET) between the two methods when comparing T based on corrected and uncorrected LE. Overall, our results demonstrate the existence of a high RH bias in water fluxes in the FLUXNET2015 dataset and suggest that this bias is a pronounced source of uncertainty in ET measurements to be considered when estimating ecosystem T/ET and WUE.
Tests were conducted on a DM10 vitrification system with prototypical off-gas treatment system, which includes an SBS, WESP, and evaporator based on the design of the evaporator to be installed at the WTP for concentration of the liquid effluents. This allowed determination of the partitioning and speciation of iodine between the melter and the off gas system components, including liquid effluents from the SBS and WESP as well as in the evaporator condensate and concentrate. Evaporator testing was decoupled from melter testing to permit filtration and pH adjustments of process solutions prior to evaporation. In addition, a slip stream was pulled from the exhaust downstream of the WESP and High-Efficiency Particulate Air (HEPA) filters and passed through a caustic scrubber simulating the WTP caustic scrubber to assess iodine partitioning to the caustic scrubber liquid effluent. The tests were conducted using simulated Hanford LAW from tank AP-107, which is the planned first feed for Direct Feed LAW (DFLAW) operations, at a nominal feed concentration of 5.6 molar Na over about 120 hours of testing.
The methods are described for calibrating, selecting filter weights, filtering, and computing filter response functions. These methods are computed on a statistical analyzer (STAN) system with a Honeywell DDP-116 central processor. The following filter types are computed: all pass, low pass, high pass, band pass, band rejection, and derivative.
Robot turned off if acceleration exceeds preset value. Signals from accelerometer on robot arm pass through filter and amplifier, eliminating high-frequency noise and hydraulic-pump pulsations. Data digitized and processed in computer. Unit controls other machines that perform repetitive movements, including rotary tables, tracked vehicles, conveyor lines, and elevators.